Development of the Wearable Device to Measure a Floor Reacting Force

Michihiko Fukunaga, Hayato Ichinose, Shogo Ishizaka
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Abstract

The objective of this study is to measure a floor reacting force by the wearable device. We attached six pressure sensors under a sole and created the estimating equation of floor reacting force using the sensor outputs by the data stepping on a force plate. Estimation was tried by the stepping motion and a normal gait. We tried four types of estimating equation: multiple coefficients or a single coefficient and individual or general, respectively. As a result, the errors were minimum during the expecting motion with multiple and individual coefficients. However, the errors increased too much during unexpected motions. In case of such motions, estimation with a single coefficient would rather better. Moreover, using the general estimating equation for any test subjects, estimation with multiple coefficients could not reduce the errors much relative to the case with a single coefficient. These results indicated that using many explanatory variables might be good for a limited condition, however, a few variables might be enough for covering a wide range of situations, motions or test subjects. After all, using a generalized estimating equation, the estimation error was about 20kgf on average, which is too large for using on rehabilitation. Our future plan is to reduce the errors by using individual parameters or using multiple formulas determining which one is proper to use automatically.
可穿戴式地板反作用力测量装置的研制
本研究的目的是通过可穿戴设备测量地板反作用力。我们在鞋底下安装了6个压力传感器,利用传感器输出的数据踩在力板上,建立了底板反作用力的估计方程。通过步进运动和正常步态进行估计。我们分别尝试了四种类型的估计方程:多系数或单系数,个体或一般。结果表明,在多系数和单个系数的期望运动中,误差最小。然而,在意外运动中,误差增加太多。在这种情况下,用单个系数估计会更好。而且,对于任何被试的一般估计方程,多系数估计与单系数估计相比,误差减小的幅度并不大。这些结果表明,使用许多解释变量可能对有限的条件有好处,然而,一些变量可能足以涵盖广泛的情况,动作或测试对象。毕竟,使用广义估计方程,估计误差平均约为20kgf,这对于用于康复治疗来说太大了。我们未来的计划是通过使用单个参数或使用多个公式来减少误差,自动确定哪一个是合适的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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